Aiko Inoue
Impact in
- Cancer Research top 10%
- Protease and Inhibitor Mechanisms
- Geriatrics and Gerontology top 10%
Papers in
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- Muscle Physiology and Disorders 11
- S100 Proteins and Annexins 4
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- Protease and Inhibitor Mechanisms 12
- Co-authors
- Masafumi Kuzuya (42 shared papers)Xian Wu Cheng (35 shared papers)Lina Hu (22 shared papers)Kenji Okumura (16 shared papers)Toyoaki Murohara (20 shared papers)Guo‐Ping Shi (18 shared papers)Takeshi Sasaki (11 shared papers)Hongxian Wu (13 shared papers)
- Journals
- Journal of the American Heart Association (5 papers)Hypertension (4 papers)Journal of Cachexia Sarcopenia and Muscle (4 papers)Journal of Hypertension (3 papers)International Journal of Cardiology (3 papers)
- Partner nations
- JapanChinaUnited States
In The Last Decade
Aiko Inoue
52 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 104
- Cancer Research 231
- Geriatrics and Gerontology 48
- Rehabilitation 77
- Physiology 289
- Endocrinology, Diabetes and Metabolism 168
Countries citing papers authored by Aiko Inoue
This map shows the geographic impact of Aiko Inoue's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Aiko Inoue with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aiko Inoue more than expected).
Fields of papers citing papers by Aiko Inoue
This network shows the impact of papers produced by Aiko Inoue. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Aiko Inoue. The network helps show where Aiko Inoue may publish in the future.
Co-authors
The 25 scholars most cited alongside Aiko Inoue, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 86 | |
| 2 | 2014 | 75 | |
| 3 | 2017 | 68 | |
| 4 | 2016 | 65 | |
| 5 | 2017 | 60 | |
| 6 | 2017 | 59 | |
| 7 | 2011 | 52 | |
| 8 | 2014 | 46 | |
| 9 | 2019 | 44 | |
| 10 | 2009 | 42 | |
| 11 | 2013 | 41 | |
| 12 | 2007 | 39 | |
| 13 | 2017 | 38 | |
| 14 | 2020 | 38 | |
| 15 | 2022 | 37 | |
| 16 | 2023 | 34 | |
| 17 | 2017 | 33 | |
| 18 | 2015 | 29 | |
| 19 | 2019 | 28 | |
| 20 | 2010 | 24 |
About Aiko Inoue
Aiko Inoue is a scholar working on Molecular Biology, Cancer Research, Physiology, Cardiology and Cardiovascular Medicine and Surgery, having authored 56 papers that have together received 1.3k indexed citations. Recurring topics across this work include Protease and Inhibitor Mechanisms (12 papers), Muscle Physiology and Disorders (11 papers), Nutrition and Health in Aging (9 papers), Cell Adhesion Molecules Research (4 papers), S100 Proteins and Annexins (4 papers), Exercise and Physiological Responses (4 papers), Cardiovascular, Neuropeptides, and Oxidative Stress Research (4 papers) and Adipokines, Inflammation, and Metabolic Diseases (4 papers). The work is most often cited by research in Cancer Research (231 citations), Geriatrics and Gerontology (48 citations), Rehabilitation (77 citations), Physiology (289 citations) and Endocrinology, Diabetes and Metabolism (168 citations). Aiko Inoue has collaborated with scholars based in Japan, China and United States. Frequent co-authors include Masafumi Kuzuya, Xian Wu Cheng, Lina Hu, Kenji Okumura, Toyoaki Murohara, Guo‐Ping Shi, Takeshi Sasaki, Hongxian Wu, Yanna Lei and Limei Piao. Their work appears in journals such as Journal of the American Heart Association, Hypertension, Journal of Cachexia Sarcopenia and Muscle, Journal of Hypertension and International Journal of Cardiology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.